Background: Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or su...
We propose in this paper an exploratory analysis algorithm for functional data. The method partitions a set of functions into K clusters and represents each cluster by a simple pr...
The Markov Random Walk model has been recently exploited for multi-document summarization by making use of the link relationships between sentences in the document set, under the ...
Abstract In data clustering, many approaches have been proposed. For example, K-means method and hierarchical method. A problem is in effect by initial value and criterion to comb...
In this paper, we propose the combination of the Self Organizing Map (SOM) and of the tangent distance for effective clustering in Document Image Analysis. The proposed model (SOM...